Why this role stands out
As a Software Intern in Ginkgo Bioworks' Autonomous Lab, you'll develop the digital brain of a cutting-edge, 24/7 robotic lab, enabling "Protocols as Code" and building an AI scientist. This role is perfect for those eager to apply software skills to physical systems or computational biology, offering invaluable experience in a revolutionary field. Apply now to be part of shaping the future of bioengineering!
Quick overview
Job description
Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms.
About the Role: Ginkgo Bioworks is constructing the world’s first "Total Autonomous Lab"—a facility where scientific work is requested by code and executed by robots, 24/7. We are looking for a Software Intern to help build the digital brain of this lab. You will work with Catalyst, our proprietary software stack that orchestrates fleets of Reconfigurable Automation Cells (RACs). This role is ideal for software engineers who want to apply their skills to physical systems or computational biologists who want to move beyond analysis into autonomous execution.
Responsibilities:
- Enable "Protocols as Code": Develop and refine Python-based protocols using the Catalyst Client to control liquid handlers, plate readers, and robotic arms.
- Build the AI Scientist: Assist in the development of Catalyst Agent, our LLM-based interface that allows scientists to launch experiments using natural language.
- Integrate Lab Data: Work on data pipelines that automatically harvest, structure, and upload experimental data from RACs into our data lake for AI model training.
- Develop Device Drivers: Help integrate new hardware instruments into the Catalyst ecosystem, writing the drivers that allow our software to "talk" to new lab tools.
Preferred Qualifications:
- No college degree necessary but some skills in coding or related areas required.
- Strong proficiency in Python; experience with hardware control or APIs is a plus.
- Enthusiasm for "Lab-in-the-Loop" technologies where AI models drive physical experimentation.
- Interest in biological data standards and laboratory automation.
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